✨Rethinking the Value of Agent-Generated Tests for LLM-Based Software Engineering Agents
📝 Summary:
This study finds that agent-generated tests for LLM software engineering agents may have limited value. Test writing frequency doesnt correlate with issue resolution, and agents prefer informal print statements. Varying test volume showed little impact, suggesting marginal utility in current prac...
🔹 Publication Date: Published on Feb 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07900
• PDF: https://arxiv.org/pdf/2602.07900
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#LLMAgents #SoftwareEngineering #AutomatedTesting #AIResearch #GenerativeAI
📝 Summary:
This study finds that agent-generated tests for LLM software engineering agents may have limited value. Test writing frequency doesnt correlate with issue resolution, and agents prefer informal print statements. Varying test volume showed little impact, suggesting marginal utility in current prac...
🔹 Publication Date: Published on Feb 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.07900
• PDF: https://arxiv.org/pdf/2602.07900
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#LLMAgents #SoftwareEngineering #AutomatedTesting #AIResearch #GenerativeAI
✨How Do Decoder-Only LLMs Perceive Users? Rethinking Attention Masking for User Representation Learning
📝 Summary:
This paper studies attention masking in decoder-only LLMs for user representation. It proposes Gradient-Guided Soft Masking GGSM to stabilize training when transitioning to bidirectional attention. GGSM yields higher quality user representations on industrial benchmarks.
🔹 Publication Date: Published on Feb 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10622
• PDF: https://arxiv.org/pdf/2602.10622
• Github: https://github.com/JhCircle/Deepfind-GGSM
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#LLMs #UserRepresentation #AttentionMasking #NLP #AI
📝 Summary:
This paper studies attention masking in decoder-only LLMs for user representation. It proposes Gradient-Guided Soft Masking GGSM to stabilize training when transitioning to bidirectional attention. GGSM yields higher quality user representations on industrial benchmarks.
🔹 Publication Date: Published on Feb 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10622
• PDF: https://arxiv.org/pdf/2602.10622
• Github: https://github.com/JhCircle/Deepfind-GGSM
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#LLMs #UserRepresentation #AttentionMasking #NLP #AI
This media is not supported in your browser
VIEW IN TELEGRAM
✨VidVec: Unlocking Video MLLM Embeddings for Video-Text Retrieval
📝 Summary:
VidVec uses intermediate MLLM layers for zero-shot video-text retrieval. A novel text-based alignment, mapping video captions to summaries, learns embeddings without visual supervision. It achieves state-of-the-art results on video retrieval benchmarks.
🔹 Publication Date: Published on Feb 8
🔹 Paper Links:
• arXiv Page: https://www.arxiv.org/abs/2602.08099
• PDF: https://arxiv.org/pdf/2602.08099
• Project Page: https://iyttor.github.io/VidVec
• Github: https://iyttor.github.io/VidVec
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#VideoTextRetrieval #MLLM #Embeddings #ZeroShotLearning #AI
📝 Summary:
VidVec uses intermediate MLLM layers for zero-shot video-text retrieval. A novel text-based alignment, mapping video captions to summaries, learns embeddings without visual supervision. It achieves state-of-the-art results on video retrieval benchmarks.
🔹 Publication Date: Published on Feb 8
🔹 Paper Links:
• arXiv Page: https://www.arxiv.org/abs/2602.08099
• PDF: https://arxiv.org/pdf/2602.08099
• Project Page: https://iyttor.github.io/VidVec
• Github: https://iyttor.github.io/VidVec
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#VideoTextRetrieval #MLLM #Embeddings #ZeroShotLearning #AI
✨Graph-Enhanced Deep Reinforcement Learning for Multi-Objective Unrelated Parallel Machine Scheduling
📝 Summary:
A PPO-GNN Deep Reinforcement Learning framework solves multi-objective parallel machine scheduling. It balances total weighted tardiness and total setup time, outperforming traditional methods with a superior trade-off.
🔹 Publication Date: Published on Feb 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08052
• PDF: https://arxiv.org/pdf/2602.08052
• Project Page: https://bulentsoykan.github.io/GNN-DRL4UPMSP/
• Github: https://github.com/bulentsoykan/GNN-DRL4UPMSP
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
A PPO-GNN Deep Reinforcement Learning framework solves multi-objective parallel machine scheduling. It balances total weighted tardiness and total setup time, outperforming traditional methods with a superior trade-off.
🔹 Publication Date: Published on Feb 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08052
• PDF: https://arxiv.org/pdf/2602.08052
• Project Page: https://bulentsoykan.github.io/GNN-DRL4UPMSP/
• Github: https://github.com/bulentsoykan/GNN-DRL4UPMSP
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning
📝 Summary:
ECHO-2 is a distributed reinforcement learning framework that enables efficient post-training of large language models by overlapping rollout generation, dissemination, and training while managing pol...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02192
• PDF: https://arxiv.org/pdf/2602.02192
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
ECHO-2 is a distributed reinforcement learning framework that enables efficient post-training of large language models by overlapping rollout generation, dissemination, and training while managing pol...
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02192
• PDF: https://arxiv.org/pdf/2602.02192
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨Reasoning Cache: Continual Improvement Over Long Horizons via Short-Horizon RL
📝 Summary:
RC, an iterative decoding algorithm, enables large language models to extrapolate and continuously improve beyond training budgets by constructing reasoning chains that enhance across iterations, achi...
🔹 Publication Date: Published on Feb 3
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.03773
• PDF: https://arxiv.org/pdf/2602.03773
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
RC, an iterative decoding algorithm, enables large language models to extrapolate and continuously improve beyond training budgets by constructing reasoning chains that enhance across iterations, achi...
🔹 Publication Date: Published on Feb 3
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.03773
• PDF: https://arxiv.org/pdf/2602.03773
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨StealthRL: Reinforcement Learning Paraphrase Attacks for Multi-Detector Evasion of AI-Text Detectors
📝 Summary:
StealthRL is a reinforcement learning framework that creates adversarial paraphrases to evade multiple AI-text detectors while preserving meaning. It achieves near-zero detection, exposing significant robustness gaps and shared architectural vulnerabilities in current AI-text detection systems.
🔹 Publication Date: Published on Feb 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08934
• PDF: https://arxiv.org/pdf/2602.08934
• Github: https://github.com/suraj-ranganath/StealthRL
🔹 Models citing this paper:
• https://huggingface.co/suraj-ranganath/StealthRL
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
StealthRL is a reinforcement learning framework that creates adversarial paraphrases to evade multiple AI-text detectors while preserving meaning. It achieves near-zero detection, exposing significant robustness gaps and shared architectural vulnerabilities in current AI-text detection systems.
🔹 Publication Date: Published on Feb 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08934
• PDF: https://arxiv.org/pdf/2602.08934
• Github: https://github.com/suraj-ranganath/StealthRL
🔹 Models citing this paper:
• https://huggingface.co/suraj-ranganath/StealthRL
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
❤1
✨GameDevBench: Evaluating Agentic Capabilities Through Game Development
📝 Summary:
GameDevBench is introduced as the first benchmark for evaluating agents on game development tasks that combine software development complexity with deep multimodal understanding requirements. AI-gener...
🔹 Publication Date: Published on Feb 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11103
• PDF: https://arxiv.org/pdf/2602.11103
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
GameDevBench is introduced as the first benchmark for evaluating agents on game development tasks that combine software development complexity with deep multimodal understanding requirements. AI-gener...
🔹 Publication Date: Published on Feb 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11103
• PDF: https://arxiv.org/pdf/2602.11103
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
❤1
✨Latent Thoughts Tuning: Bridging Context and Reasoning with Fused Information in Latent Tokens
📝 Summary:
Latent Thoughts Tuning introduces a novel framework for robust reasoning in continuous latent space. It addresses feature collapse by fusing contextual hidden states with predictive semantic guidance. This method outperforms baselines and achieves improved reasoning accuracy.
🔹 Publication Date: Published on Feb 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10229
• PDF: https://arxiv.org/pdf/2602.10229
• Github: https://github.com/NeosKnight233/Latent-Thoughts-Tuning
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
Latent Thoughts Tuning introduces a novel framework for robust reasoning in continuous latent space. It addresses feature collapse by fusing contextual hidden states with predictive semantic guidance. This method outperforms baselines and achieves improved reasoning accuracy.
🔹 Publication Date: Published on Feb 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10229
• PDF: https://arxiv.org/pdf/2602.10229
• Github: https://github.com/NeosKnight233/Latent-Thoughts-Tuning
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨LiveMedBench: A Contamination-Free Medical Benchmark for LLMs with Automated Rubric Evaluation
📝 Summary:
LiveMedBench addresses limitations in medical LLM evaluation by providing a continuously updated, contamination-free benchmark with rubric-based evaluation that better aligns with expert clinical reas...
🔹 Publication Date: Published on Feb 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10367
• PDF: https://arxiv.org/pdf/2602.10367
• Project Page: https://zhilingyan.github.io/LiveMedBench/
• Github: https://github.com/ZhilingYan/LiveMedBench
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
LiveMedBench addresses limitations in medical LLM evaluation by providing a continuously updated, contamination-free benchmark with rubric-based evaluation that better aligns with expert clinical reas...
🔹 Publication Date: Published on Feb 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10367
• PDF: https://arxiv.org/pdf/2602.10367
• Project Page: https://zhilingyan.github.io/LiveMedBench/
• Github: https://github.com/ZhilingYan/LiveMedBench
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨TIC-VLA: A Think-in-Control Vision-Language-Action Model for Robot Navigation in Dynamic Environments
📝 Summary:
TIC-VLA is a latency-aware framework enhancing robot navigation by explicitly modeling delayed semantic reasoning. It uses a delayed semantic-control interface and latency-consistent training. This allows robots to maintain real-time control despite significant reasoning delays.
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02459
• PDF: https://arxiv.org/pdf/2602.02459
• Project Page: https://ucla-mobility.github.io/TIC-VLA/
• Github: https://github.com/ucla-mobility/TIC-VLA
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
TIC-VLA is a latency-aware framework enhancing robot navigation by explicitly modeling delayed semantic reasoning. It uses a delayed semantic-control interface and latency-consistent training. This allows robots to maintain real-time control despite significant reasoning delays.
🔹 Publication Date: Published on Feb 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.02459
• PDF: https://arxiv.org/pdf/2602.02459
• Project Page: https://ucla-mobility.github.io/TIC-VLA/
• Github: https://github.com/ucla-mobility/TIC-VLA
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨From Features to Actions: Explainability in Traditional and Agentic AI Systems
📝 Summary:
This paper compares static and agentic AI explainability. It finds attribution methods reliable for static predictions but not for diagnosing failures in multi-step agentic systems. Trace-based diagnostics effectively localize agentic breakdowns, urging a shift to trajectory-level explainability.
🔹 Publication Date: Published on Feb 6
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.06841
• PDF: https://arxiv.org/pdf/2602.06841
• Project Page: https://vectorinstitute.github.io/unified-xai-evaluation-framework/
• Github: https://github.com/VectorInstitute/unified-xai-evaluation-framework
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
This paper compares static and agentic AI explainability. It finds attribution methods reliable for static predictions but not for diagnosing failures in multi-step agentic systems. Trace-based diagnostics effectively localize agentic breakdowns, urging a shift to trajectory-level explainability.
🔹 Publication Date: Published on Feb 6
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.06841
• PDF: https://arxiv.org/pdf/2602.06841
• Project Page: https://vectorinstitute.github.io/unified-xai-evaluation-framework/
• Github: https://github.com/VectorInstitute/unified-xai-evaluation-framework
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
Media is too big
VIEW IN TELEGRAM
✨GigaBrain-0.5M*: a VLA That Learns From World Model-Based Reinforcement Learning
📝 Summary:
GigaBrain-0.5M enhances vision-language-action models by integrating world model-based reinforcement learning. This improves performance by 30% on complex robotic tasks and enables reliable long-horizon execution, overcoming prior VLA limitations.
🔹 Publication Date: Published on Feb 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12099
• PDF: https://arxiv.org/pdf/2602.12099
• Project Page: https://gigabrain05m.github.io/
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
GigaBrain-0.5M enhances vision-language-action models by integrating world model-based reinforcement learning. This improves performance by 30% on complex robotic tasks and enables reliable long-horizon execution, overcoming prior VLA limitations.
🔹 Publication Date: Published on Feb 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12099
• PDF: https://arxiv.org/pdf/2602.12099
• Project Page: https://gigabrain05m.github.io/
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨Learning beyond Teacher: Generalized On-Policy Distillation with Reward Extrapolation
📝 Summary:
On-policy distillation is extended through a generalized framework that introduces flexible reference models and reward scaling factors, demonstrating improved performance through reward extrapolation...
🔹 Publication Date: Published on Feb 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12125
• PDF: https://arxiv.org/pdf/2602.12125
• Github: https://github.com/RUCBM/G-OPD
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
On-policy distillation is extended through a generalized framework that introduces flexible reference models and reward scaling factors, demonstrating improved performance through reward extrapolation...
🔹 Publication Date: Published on Feb 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12125
• PDF: https://arxiv.org/pdf/2602.12125
• Github: https://github.com/RUCBM/G-OPD
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨Unveiling Implicit Advantage Symmetry: Why GRPO Struggles with Exploration and Difficulty Adaptation
📝 Summary:
Asymmetric Group Relative Advantage Estimation addresses exploration and difficulty adaptation challenges in reinforcement learning with large language models by dynamically modulating exploration inc...
🔹 Publication Date: Published on Feb 5
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.05548
• PDF: https://arxiv.org/pdf/2602.05548
• Github: https://github.com/HKU-HealthAI/A-GRAE
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
Asymmetric Group Relative Advantage Estimation addresses exploration and difficulty adaptation challenges in reinforcement learning with large language models by dynamically modulating exploration inc...
🔹 Publication Date: Published on Feb 5
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.05548
• PDF: https://arxiv.org/pdf/2602.05548
• Github: https://github.com/HKU-HealthAI/A-GRAE
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨Budget-Constrained Agentic Large Language Models: Intention-Based Planning for Costly Tool Use
📝 Summary:
Budget-constrained tool-augmented agents use a hierarchical world model and intent-aware planning to optimize multi-step task completion under monetary constraints. AI-generated summary We study budge...
🔹 Publication Date: Published on Feb 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11541
• PDF: https://arxiv.org/pdf/2602.11541
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
Budget-constrained tool-augmented agents use a hierarchical world model and intent-aware planning to optimize multi-step task completion under monetary constraints. AI-generated summary We study budge...
🔹 Publication Date: Published on Feb 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11541
• PDF: https://arxiv.org/pdf/2602.11541
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨Dreaming in Code for Curriculum Learning in Open-Ended Worlds
📝 Summary:
Foundation models generate executable environment code to scaffold learning progress in open-ended worlds, enabling agents to acquire long-horizon skills through curriculum control. AI-generated summa...
🔹 Publication Date: Published on Feb 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08194
• PDF: https://arxiv.org/pdf/2602.08194
• Project Page: https://konstantinosmitsides.github.io/dreaming-in-code
• Github: https://github.com/konstantinosmitsides/dreaming-in-code
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
Foundation models generate executable environment code to scaffold learning progress in open-ended worlds, enabling agents to acquire long-horizon skills through curriculum control. AI-generated summa...
🔹 Publication Date: Published on Feb 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.08194
• PDF: https://arxiv.org/pdf/2602.08194
• Project Page: https://konstantinosmitsides.github.io/dreaming-in-code
• Github: https://github.com/konstantinosmitsides/dreaming-in-code
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨Neural Additive Experts: Context-Gated Experts for Controllable Model Additivity
📝 Summary:
Neural Additive Experts combines multiple specialized networks with a dynamic gating mechanism to balance predictive accuracy and feature interpretability in machine learning models. AI-generated summ...
🔹 Publication Date: Published on Feb 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10585
• PDF: https://arxiv.org/pdf/2602.10585
• Github: https://github.com/Teddy-XiongGZ/NAE
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
Neural Additive Experts combines multiple specialized networks with a dynamic gating mechanism to balance predictive accuracy and feature interpretability in machine learning models. AI-generated summ...
🔹 Publication Date: Published on Feb 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.10585
• PDF: https://arxiv.org/pdf/2602.10585
• Github: https://github.com/Teddy-XiongGZ/NAE
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨The Devil Behind Moltbook: Anthropic Safety is Always Vanishing in Self-Evolving AI Societies
📝 Summary:
Multi-agent LLM systems cannot achieve continuous self-improvement and maintain safety if isolated. Isolated self-evolution causes statistical blind spots, leading to irreversible safety degradation. This is a fundamental limit, requiring external oversight or new safety mechanisms.
🔹 Publication Date: Published on Feb 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.09877
• PDF: https://arxiv.org/pdf/2602.09877
✨ Datasets citing this paper:
• https://huggingface.co/datasets/xunyoyo/Self-Evolving-Safety
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
Multi-agent LLM systems cannot achieve continuous self-improvement and maintain safety if isolated. Isolated self-evolution causes statistical blind spots, leading to irreversible safety degradation. This is a fundamental limit, requiring external oversight or new safety mechanisms.
🔹 Publication Date: Published on Feb 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.09877
• PDF: https://arxiv.org/pdf/2602.09877
✨ Datasets citing this paper:
• https://huggingface.co/datasets/xunyoyo/Self-Evolving-Safety
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨LawThinker: A Deep Research Legal Agent in Dynamic Environments
📝 Summary:
LawThinker is an autonomous legal research agent that uses an Explore-Verify-Memorize strategy with a DeepVerifier module to ensure accurate and procedurally compliant legal reasoning through dynamic ...
🔹 Publication Date: Published on Feb 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12056
• PDF: https://arxiv.org/pdf/2602.12056
• Github: https://github.com/yxy-919/LawThinker-agent
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
LawThinker is an autonomous legal research agent that uses an Explore-Verify-Memorize strategy with a DeepVerifier module to ensure accurate and procedurally compliant legal reasoning through dynamic ...
🔹 Publication Date: Published on Feb 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.12056
• PDF: https://arxiv.org/pdf/2602.12056
• Github: https://github.com/yxy-919/LawThinker-agent
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
✨Voxtral Realtime
📝 Summary:
Voxtral Realtime is a streaming speech recognition model trained end-to-end for sub-second latency with performance matching offline systems. AI-generated summary We introduce Voxtral Realtime, a nati...
🔹 Publication Date: Published on Feb 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11298
• PDF: https://arxiv.org/pdf/2602.11298
• Project Page: https://mistral.ai/news/voxtral-transcribe-2
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
Voxtral Realtime is a streaming speech recognition model trained end-to-end for sub-second latency with performance matching offline systems. AI-generated summary We introduce Voxtral Realtime, a nati...
🔹 Publication Date: Published on Feb 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.11298
• PDF: https://arxiv.org/pdf/2602.11298
• Project Page: https://mistral.ai/news/voxtral-transcribe-2
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research